Fast multi-contrast MRI reconstruction

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 7510 LNCS, Issue , 2012, Pages 281-288

  Huang, Junzhou ^a   Chen, Chen ^a   Axel, Leon ^b  

^a University of Texas at Arlington   (United States)

^b NEW YORK UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ITERATIVE METHODS; MAGNETIC RESONANCE IMAGING; MEDICAL COMPUTING; MEDICAL IMAGING;

ITERATIVE FRAMEWORK; LINEAR COMBINATIONS; MRI RECONSTRUCTION; RECONSTRUCTED IMAGE; SIMULTANEOUS RECONSTRUCTION; SPARSITY REGULARIZATIONS; TV REGULARIZATIONS; WAVELET COEFFICIENTS;

IMAGE RECONSTRUCTION;

ALGORITHM; ARTICLE; BAYES THEOREM; BRAIN; BRAIN MAPPING; COMPUTER PROGRAM; COMPUTER SIMULATION; HUMAN; IMAGE PROCESSING; METHODOLOGY; NUCLEAR MAGNETIC RESONANCE IMAGING; PATHOLOGY; REPRODUCIBILITY; THEORETICAL MODEL; TIME;

ALGORITHMS; BAYES THEOREM; BRAIN; BRAIN MAPPING; COMPUTER SIMULATION; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; MODELS, THEORETICAL; REPRODUCIBILITY OF RESULTS; SOFTWARE; TIME FACTORS;

MLCS; MLOWN;

EID: 84872536580     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-33415-3_35     Document Type: Conference Paper

References (14)

1. Donoho, D.: Compressed sensing. IEEE Transactions on Information Theory 52(4), 1289–1306 (2006)
2. Lustig, M., Donoho, D., Pauly, J.: Sparse MRI: The application of compressed sensing for rapid MR imaging. Magnetic Resonance in Medicine 58, 1182–1195 (2007)
3. Ma, S., Yin, W., Zhang, Y., Chakraborty, A.: An efficient algorithm for compressed MR imaging using total variation and wavelets. In: Proceedings of CVPR (2008)
4. Yang, J., Zhang, Y., Yin, W.: A fast alternating direction method for TVL1-L2 signal reconstruction from partial fourier data. IEEE Journal of Selected Topics in Signal Processing, Special Issue on Compressive Sensing 4(2) (2010)
5. Huang, J., Zhang, S., Metaxas, D.: Efficient MR Image Reconstruction for Compressed MR Imaging. In: Jiang, T., Navab, N., Pluim, J.P.W., Viergever, M.A. (eds.) MICCAI 2010, Part I. LNCS, vol. 6361, pp. 135–142. Springer, Heidelberg (2010)
6. Huang, J., Zhang, S., Metaxas, D.: Efficient MR image reconstruction for compressed MR imaging. Medical Image Analysis 15, 670–679 (2011)
7. Huang, J., Zhang, T.: The benefit of group sparsity. Annals of Statistics 38, 1978– 2004 (2010)
8. Majumdar, A., Ward, R.: Joint reconstruction of multiecho MR images using correlated sparsity. Magnetic Resonance Imaging 29, 899–906 (2011)
9. Bilgic, B., Goyal, V., Adalsteinsson, E.: Multi-contrast reconstruction with bayesian compressed sensing. Magnetic Resonance Medicine 66, 1601–1615 (2011)
10. Ji, S., Dunson, D., Carin, L.: Multitask compressive sensing. IEEE Transactions on Signal Processing 57, 92–106 (2009)
11. Berg, E., Friedlander, M.: Probing the pareto frontier for basis pursuit solutions. SIAM Journal on Scientific Computing 31, 890–912 (2008)
12. Beck, A., Teboulle, M.: Fast gradient-based algorithms for constrained total variation image denoising and deblurring problems. IEEE Transaction on Image Processing 18(113), 2419–2434 (2009)
13. Rohlfing, T., Zahr, N.M., Sullivan, E., Pfefferbaum, A.: The sri24 multichannel atlas of normal adult human brain structure. Human Brain Mapping 31, 798–819 (2010)
14. Wang, Z., Bovik, A.C., Sheikh, H.R., Simoncelli, E.P.: Image quality assessment: From error measurement to structural similarit. IEEE Transactions on Image Processing 13(4), 600–612 (2004)